Differential opinions among Hong Kong online social media, traditional news media, opinion polls and the government consultations on methods for selecting chief executive in 2017

Communication among Hong Kong Facebook Pages during the #umbrellarevolution

Chung-hong Chan, King-wa FuJournalism and Media Studies Centre, HKUCeDEM-Asia 2014 @chainsawriot

Credit: NOW TV, RFA, news.com.au, Forbes

Traditional media

Social Media / Online Media

What we know #1

Online Media

Social Media

18-29yTert. Ed

30-49yS3-S7

>60y<S3

Source: CUHK COMvia Ming Pao

Fu KW, Chan CH. Analyzing Online Sentiment to Predict Opinion Poll Results. Cyberpsychol Behav Soc Netw. 2013 Sep;16(9):702-7

What we know #2

Conover MD et al.Political Polarization on Twitter.ICWSM 2011

What we know #3

What we don’t know

1. Polarization of online social media in Hong Kong

2. How this polarization affects the relationship between online sentiment and public opinion in Hong Kong?

Data source

● Facebook pages about HK(n=885)● Snowball sampling (still growing!)● Publicly available posts from included pages ● from 2014-07-01 (day 1 of the research) to

2014-11-10

Facebook sharing network

weighted: number of sharing

Why sharing network?

● Castells (1996, 2009): ‘Network society’● [Communication] Power-making in a network

‘Switchers’: who exercise the ability to connect and coordinate different actors in the network by sharing common interests, values, goals, resources, or cultural materials

● Farrells & Drezner (2008): Bottom-up agenda setting

Two‐Step Flow Model of Influence Network model of influence

Watts D, Dodds PS. Influentials, Networks, and Public Opinion Formation. J Consumer Res. 2007 34

Network and public opinion formation

Sharing network

Betweenness

Betweenness:how often a node is located on the shortest path between nodes in the network

Interpretation:● ‘Facilitator’ of

communication within the network

● Influence over what flow and does not in the network

Nodes with >95pct betweenness(Node size: betweeness)

Subgraph

1-Inmedia

2-Kengo Ip健吾3-Scholarism

4-Apple Daily

5-HKFS

Subgraph

Nodes with >95pct betweenness(Node size: betweeness)

Polarization

Conover MD et al.Political Polarization on Twitter.ICWSM 2011

Walktrap community detection algo.

● “Clustering”● Random walker tends to be trapped in the

densely connected parts (a.k.a. hidden community) within the network

Pon P, Latapy M.Computing communities in Large Networks Using Random Walk.ISCIS 2005

Hidden communities found

Six large (> 10 nodes) hidden communities found1. Giant component (364 nodes)2. Activists (208 nodes)3. ProBJ #1 (16 nodes)4. Autonomists (87 nodes)5. ProBJ #2 (27 nodes)6. Trivia (17 nodes)

Community 1: Giant component

Size: 364 nodes

Node with top3 betweenness: 健吾 (Kengo Ip)學民思潮 (Scholarism)蘋果日報 (Apple Daily)

Keywords:

app, itunes, play, download, google, 真話, egyiyl, 憐憫, memehkdotcom, me

Community 2: Activists

Size: 208 nodes

Node with top3 betweenness: 獨立媒體 (Inmedia)學聯 (HKFS)和平佔中 (OLPC)

Keywords:

即時, hkclassboycott, 現場, occupycentral, 我們, hongkong, 澳門, umbrellamovement, 採訪, 詳看

Community 3: Probeijing 1

Size: 16 nodes

Node with top3 betweenness: 我哋係中國香港人 (we are Chinese in Hong Kong)幫港出聲(Silent Majority)香港培青社 (HK Youth Development Society)

Keywords:

天有, admin, 管理員, 豫行, 白少, 簽名, 親眼看到, wechat, 中國, 圖像

Community 4: Autonomists

Size: 87 nodes

Node with top3 betweenness: 熱血時報(Passion Times)有種美德叫有種 (a blogger)無待堂 (a blogger)

Keywords:

熱血, 制憲, 課金, 時報, 文青, 育成, 抗共, 同步, 打倒, 主持

Community 5: Probeijing 2

Size: 27 nodes

Node with top3 betweenness: 時聞香港(Hong Kong Good News)向香港警察致敬 (Salute to Hong Kong Police)理性撐國民教育 (Rationally support National Education)

Keywords:

Community 6: Trivia

Size: 17 nodes

Node with top3 betweenness: 我係香港人(We are Hong Konger)香港地笑話(Hong Kong Jokes)投考公務員資訊 (Information for Civil Service Recruitment)

Keywords:

詳情, 面試, 招聘, 開課, graceyard, edu, 二級, 開班, 筆試, 主任

Overall FB volume and predictionof CY’s rating using different lag units in day.

(after cancel out the effect of autocorrelation and seasonality usingARIMA (1,1,1)(1,0,0)7 model)

Frontline: ‘Activists’ pages

-0.136 (95% CI: -0.27 to -0.01)

Tracking “public opinion” using Facebook volume

“Giant”, “Activists”, “Probeijing2”

“Activists” pages activities are correlated with CY Leung’s rating in the largest lag unit. (18 days)

Preliminary: “Sentiment towards gov”

A sentiment model was trained with only 400 human-coded facebook posts (300 training, 100 validation)

Test set F1 score: 75%

Useful features associated with negative sentiment

hkclassboycott/umbrellarevolution/主席/人士/人大/人數/他們/佔中/佔領/全球/公民/原則/反佔中/呼籲/和平/基本法/報告/如何/學生/學聯/對話/市民/很多/感到/批評/抗爭/支持/政府/政改/政治/日本/旺角/普選/服務/未有/梁振英/民主/民意/沒有/清場/港人/爭取/特首/現場/現時/發起人/示威/示威者/社會/社民連/立法會/簽名/繼續/罷課/行動/表示/表達/認同/認為/警察/警方/議員/進行/遊行/運動/選舉/邀請/重新/金鐘/集會/難以/雨傘/革命/香港/黃之鋒

More like a political content filter

Ongoing

● Long term temporal relationship● Better sentiment filter

http://weiboscope.jmsc.hku.hk/tbj/(Coming soon!)

http://weiboscope.jmsc.hku.hk/

@chainsawriot